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EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms

Alzheimer’s disease (AD) is a progressive neuropsychiatric disease affecting many elderly people and is characterized by progressive cognitive impairment of memory, visuospatial, and executive functions. As the elderly population is growing, the number of AD patients is increasing considerably. Ther...

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Autores principales: Aoki, Yasunori, Takahashi, Rei, Suzuki, Yuki, Pascual-Marqui, Roberto D., Kito, Yumiko, Hikida, Sakura, Maruyama, Kana, Hata, Masahiro, Ishii, Ryouhei, Iwase, Masao, Mori, Etsuro, Ikeda, Manabu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998651/
https://www.ncbi.nlm.nih.gov/pubmed/36894582
http://dx.doi.org/10.1038/s41598-023-30075-3
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author Aoki, Yasunori
Takahashi, Rei
Suzuki, Yuki
Pascual-Marqui, Roberto D.
Kito, Yumiko
Hikida, Sakura
Maruyama, Kana
Hata, Masahiro
Ishii, Ryouhei
Iwase, Masao
Mori, Etsuro
Ikeda, Manabu
author_facet Aoki, Yasunori
Takahashi, Rei
Suzuki, Yuki
Pascual-Marqui, Roberto D.
Kito, Yumiko
Hikida, Sakura
Maruyama, Kana
Hata, Masahiro
Ishii, Ryouhei
Iwase, Masao
Mori, Etsuro
Ikeda, Manabu
author_sort Aoki, Yasunori
collection PubMed
description Alzheimer’s disease (AD) is a progressive neuropsychiatric disease affecting many elderly people and is characterized by progressive cognitive impairment of memory, visuospatial, and executive functions. As the elderly population is growing, the number of AD patients is increasing considerably. There is currently growing interest in determining AD’s cognitive dysfunction markers. We used exact low-resolution-brain-electromagnetic-tomography independent-component-analysis (eLORETA-ICA) to assess activities of five electroencephalography resting-state-networks (EEG-RSNs) in 90 drug-free AD patients and 11 drug-free patients with mild-cognitive-impairment due to AD (ADMCI). Compared to 147 healthy subjects, the AD/ADMCI patients showed significantly decreased activities in the memory network and occipital alpha activity, where the age difference between the AD/ADMCI and healthy groups was corrected by linear regression analysis. Furthermore, the age-corrected EEG-RSN activities showed correlations with cognitive function test scores in AD/ADMCI. In particular, decreased memory network activity showed correlations with worse total cognitive scores for both Mini-Mental-State-Examination (MMSE) and Alzheimer’s Disease-Assessment-Scale-cognitive-component-Japanese version (ADAS-J cog) including worse sub-scores for orientation, registration, repetition, word recognition and ideational praxis. Our results indicate that AD affects specific EEG-RSNs and deteriorated network activity causes symptoms. Overall, eLORETA-ICA is a useful, non-invasive tool for assessing EEG-functional-network activities and provides better understanding of the neurophysiological mechanisms underlying the disease.
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spelling pubmed-99986512023-03-11 EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms Aoki, Yasunori Takahashi, Rei Suzuki, Yuki Pascual-Marqui, Roberto D. Kito, Yumiko Hikida, Sakura Maruyama, Kana Hata, Masahiro Ishii, Ryouhei Iwase, Masao Mori, Etsuro Ikeda, Manabu Sci Rep Article Alzheimer’s disease (AD) is a progressive neuropsychiatric disease affecting many elderly people and is characterized by progressive cognitive impairment of memory, visuospatial, and executive functions. As the elderly population is growing, the number of AD patients is increasing considerably. There is currently growing interest in determining AD’s cognitive dysfunction markers. We used exact low-resolution-brain-electromagnetic-tomography independent-component-analysis (eLORETA-ICA) to assess activities of five electroencephalography resting-state-networks (EEG-RSNs) in 90 drug-free AD patients and 11 drug-free patients with mild-cognitive-impairment due to AD (ADMCI). Compared to 147 healthy subjects, the AD/ADMCI patients showed significantly decreased activities in the memory network and occipital alpha activity, where the age difference between the AD/ADMCI and healthy groups was corrected by linear regression analysis. Furthermore, the age-corrected EEG-RSN activities showed correlations with cognitive function test scores in AD/ADMCI. In particular, decreased memory network activity showed correlations with worse total cognitive scores for both Mini-Mental-State-Examination (MMSE) and Alzheimer’s Disease-Assessment-Scale-cognitive-component-Japanese version (ADAS-J cog) including worse sub-scores for orientation, registration, repetition, word recognition and ideational praxis. Our results indicate that AD affects specific EEG-RSNs and deteriorated network activity causes symptoms. Overall, eLORETA-ICA is a useful, non-invasive tool for assessing EEG-functional-network activities and provides better understanding of the neurophysiological mechanisms underlying the disease. Nature Publishing Group UK 2023-03-09 /pmc/articles/PMC9998651/ /pubmed/36894582 http://dx.doi.org/10.1038/s41598-023-30075-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Aoki, Yasunori
Takahashi, Rei
Suzuki, Yuki
Pascual-Marqui, Roberto D.
Kito, Yumiko
Hikida, Sakura
Maruyama, Kana
Hata, Masahiro
Ishii, Ryouhei
Iwase, Masao
Mori, Etsuro
Ikeda, Manabu
EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms
title EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms
title_full EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms
title_fullStr EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms
title_full_unstemmed EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms
title_short EEG resting-state networks in Alzheimer’s disease associated with clinical symptoms
title_sort eeg resting-state networks in alzheimer’s disease associated with clinical symptoms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998651/
https://www.ncbi.nlm.nih.gov/pubmed/36894582
http://dx.doi.org/10.1038/s41598-023-30075-3
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